Monday, September 1, 2014
The Cost of Forecasting Error - Walgreens Example
We’ve learned from the readings this week all of the vital factors that must go into forecasting, and how forecast models are determined. We also learned the uncertainty of forecasting and how to minimize that error. What happens when reputable company overlooks a major factor and what is the cost of forecast error?
In April of this year, the Walgreens CFO predicted $8.5 billion in pharmacy unit earnings for the end of 2016. He then lowered this prediction by $1.1 billion in July. This error caused the CFO of Walgreens and the president of the pharmacy, health and wellness division to step down. Walgreens has recently made efforts to become a larger middleman in dispensing prescription drugs under the Medicare Plan D plan. Medicare Plan D also plays a large role in Walgreens’ supply chain as it receives 25- 30% of its prescription drugs from this plan. Walgreens attributes this error to not accounting for the recent increase in the cost of generic drugs that Walgreens sells. Walgreens also had a lower pharmacy margin last quarter because of a pressure to reimburse third parties. Walgreens says it plans to find way to lower expenses to offset the decline of gross margin (50 basis points). This error also caused Walgreen’s stock to lower.
As we learned in the readings, all forecasts have a level of uncertainty, but it is important to minimize that uncertainty or even measure that level of uncertainty. It is also important to collect as much data as possible to develop the metric that you wish to forecast. Data and vital information should not be ignored while developing a forecast. Another vital component of forecasting is to integrate suppliers into the process. In this example, Walgreens left out vital information while forecasting its pharmaceutical earnings. The cost of the generic drugs that Walgreens sells should have been accounted for, as it is a major part of the supply chain. Why hadn’t Walgreens considered the cost of its suppliers? When a company has a forecasting error this large it misleads investors, causes reputational damage, disrupts the supply chain process, and in this case, causes two executives their jobs.
It is important to evaluate all factors in a supply chain while undergoing the forecasting process. Leaving out one factor can have serious consequences greater than a rounding error. This makes me question the methods that companies use to develop their forecasts and how much they can be trusted. Should we try to understand the process that they use of simply trust the information that is put out?